1. Field of the Invention
This invention generally relates to methods and systems for generating inspection results for a specimen with an adaptive nuisance filter.
2. Description of the Related Art
The following description and examples are not admitted to be prior art by virtue of their inclusion in this section.
Fabricating semiconductor devices such as logic and memory devices typically includes processing a substrate such as a semiconductor wafer using a large number of semiconductor fabrication processes to form various features and multiple levels of the semiconductor devices. For example, lithography is a semiconductor fabrication process that involves transferring a pattern from a reticle to a resist arranged on a semiconductor wafer. Additional examples of semiconductor fabrication processes include, but are not limited to, chemical-mechanical polishing, etch, deposition, and ion implantation. Multiple semiconductor devices may be fabricated in an arrangement on a single semiconductor wafer and then separated into individual semiconductor devices.
Inspection processes are used at various steps during a semiconductor manufacturing process to detect defects on wafers. Inspection processes have always been an important park of fabricating semiconductor devices such as integrated circuits. However, as the dimensions of semiconductor devices decrease, inspection processes become even more important to the successful manufacture of acceptable semiconductor devices. For instance, as the dimensions of semiconductor devices decrease, detection of defects of decreasing size has become necessary since even relatively small defects may cause unwanted aberrations in the semiconductor devices.
Inspection generally involves generating some output (e.g., images, signals, etc.) for a wafer by directing light or electrons to the wafer and detecting the light or electrons from the wafer. Once the output has been generated, defect detection is typically performed by applying some defect detection method and/or algorithm to the output. Parameters used to generate the output (e.g., optical or electron beam hardware settings), parameters used to detect the defects (e.g., defect detection algorithm settings), and any other parameters used to generate the inspection results (e.g., nuisance filter algorithm settings) are typically determined based on characteristics of the wafer and defects to be detected thereon. Most often, the goal of inspection recipe setup is to determine the parameters that will provide the highest sensitivity to defects of interest while suppressing detection of nuisance and noise on the wafer.
Inspection recipe set up can be performed in a number of different manners. For example, an inspection recipe can be trained on one or a few training wafers. However, once the inspection recipe has been generated, typically, the static inspection recipe is used indefinitely. For example, once an inspection recipe has been generated, it will typically be used indefinitely while monitoring manually the stability of the recipe, e.g., in production. Manual re-tuning of the inspection recipe may be performed when necessary. There are, however, a number of disadvantages to such approaches for using and monitoring inspection recipes. For example, the inspection recipe cannot be adjusted dynamically to process variations, tends to be unstable with respect to the nuisance rate, and can only be monitored manually.
Accordingly, it would be advantageous to develop systems and/or methods for generating inspection results for a specimen with an adaptive nuisance filter that do not have one or more of the disadvantages described above.